Coalition formation typically involves the coming together of multiple, heterogeneous, agents to achieve both their individual and collective goals. In this article, we focus on a special case of coalition formation known as Graph-Constrained Coalition ...

Rating datasets are of paramount importance in recommender systems research. They serve as input for recommendation algorithms, as simulation data, or for evaluation purposes. In the past, public accessible rating datasets were not abundantly available, ...

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a ...

Compared to constraint-based causal discovery, causal discovery based on functional causal models is able to identify the whole causal model under appropriate assumptions [Shimizu et al. 2006; Hoyer et al. 2009; Zhang and Hyvärinen 2009b]. Functional ...

In spite of the importance of activity recognition (AR) for intelligent human-computer interaction in emerging smart space applications, state-of-the-art AR technology is not ready or adequate for real-world deployments due to its insufficient accuracy. ...

Prediction markets offer an efficient market-based mechanism to aggregate large amounts of dispersed or distributed information from different people to predict the possible outcome of future events. Recently, automated prediction markets where software ...

Several approaches have been proposed for the problem of identifying authoritative actors in online communities. However, the majority of existing methods suffer from one or more of the following limitations: (1) There is a lack of an automatic ...

We propose a 6D RGB-D odometry approach that finds the relative camera pose between consecutive RGB-D frames by keypoint extraction and feature matching both on the RGB and depth image planes. Furthermore, we feed the estimated pose to the highly ...

Although the broad social and business success of recommender systems has been achieved across several domains, there is still a long way to go in terms of user satisfaction. One of the key dimensions for significant improvement is the concept of ...

In the field of visual art, metaphor is a way to communicate meaning to the viewer. We present a computational system for communicating visual metaphor that can identify adjectives for describing an image based on a low-level visual feature ...

We introduce an algorithm to automatically learn probabilistic hierarchical task networks (pHTNs) that capture a user's preferences on plans by observing only the user's behavior. HTNs are a common choice of representation for a variety of purposes in ...

The ability to model and reason about the potential violence level of a demonstration is important to the police decision making process. Unfortunately, existing knowledge regarding demonstrations is composed of partial qualitative descriptions without ...

The primary goal of this special section of ACM Transactions on Intelligent Systems and Technology is to foster research in the interplay between Social Media, Data/Opinion Mining and Search, aiming to reflect the actual developments in technologies ...

This article describes automatic methods and interactive visualizations that are tightly coupled with the goal to enable users to detect interesting portions of text document streams. In this scenario the interestingness is derived from the sentiment, ...